• Mariyamath Rifaina
• Mustafa Basthikodi
• Ahmed Rimaz Faizabadi

Parallel computing, a form of computation which allows many instructions in a program to run concurrently, in parallel. In fact to accomplish this, a program has to be split into independent parts so that each processor can execute its part of program simultaneously with the other processor. Algorithmic Species, an algorithm classification which captures low-level algorithmic details and represents them with the use of five easy way to understand array access patterns. To inscribe the challenge of parallel programming, we propose Bones. Bones is one of a source-to-source compiler that deploy on algorithmic skeletons and, a new algorithm classification. To evaluate the applicability of algorithmic species and to validate A-Darwin and Bones, we test against the HPCC benchmark. In this work, the existing species for all algorithmic classification are analyzed and some of the computationally intensive programs from HPCC benchmark have been tested using existing tools such as Bones compiler and the A-Darwin, an automatic species extraction tool. The access patterns are created for various algorithmic kernels by running against A-Darwin and the analysis is done for various code segments.

bones compiler, algorithmic species, A-Darwin tool, hpcc benchmark.

"Parallelizing program code automatically through HPCC", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.383-390, May 2019, Available :http://www.jetir.org/papers/JETIRCU06075.pdf

"Parallelizing program code automatically through HPCC", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp383-390, May 2019, Available at : http://www.jetir.org/papers/JETIRCU06075.pdf